Efficient fault-tolerant routing in IoT wireless sensor networks based on path graph flow modeling with Marchenko–Pastur distribution (EFT-PMD)

In the internet of things (IoT) based wireless sensor network (WSN), the nodes are scattered to segregate the rapt data in the relevant field of application. In general, sensor nodes of IoT possess heterogeneous property and display cluster-based routing to transmit the data as it is considered as an efficient routing method. When one or more cluster heads (CHs) fail, the sensed data of sensor nodes that are currently serving cannot be forwarded by the faulty CHs. Consequently, data of the IoT application will not be sufficiently sensed by the sink node (gateway). As a result, information processing of this field will be affected profusely. This paper focuses on the development of a paired cluster fault-tolerant disjoint path routing in a path graph and a novel approach to solve this dilemma in polynomial time of the degree of the graph. The objective of this proposed IoT–WSN architecture is to diminish the latency, end-to-end delay as well as energy consumption and thereby improving the performance in terms of throughput and packet delivery ratio. The performance of this proposed method in IoT–WSN network is measured and affirmed using benchmark network simulator.